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This paper is in the following e-collection/theme issue:

Machine Learning (3268) Clinical Informatics (2335) Imaging Informatics (479) Orthopedics (151) Medical imaging (198)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/86155, first published .
AI robot analyzing knee joint scans in a futuristic medical setting

Enhanced Magnetic Resonance Imaging–Based Knee Cartilage Segmentation Using a Swin-UNet Conditional Generative Adversarial Network: Development and Validation Study

Enhanced Magnetic Resonance Imaging–Based Knee Cartilage Segmentation Using a Swin-UNet Conditional Generative Adversarial Network: Development and Validation Study

Authors of this article:

Jun Young Park1 Author Orcid Image ;   Ji-Hoon Nam2, 3, 4 Author Orcid Image ;   Shakhboz Abdigapporov3 Author Orcid Image ;   Jong-Keun Kim5 Author Orcid Image ;   Yong-Gon Koh6 Author Orcid Image ;   Byung Woo Cho7 Author Orcid Image ;   Hyuck Min Kwon8 Author Orcid Image ;   Kwan Kyu Park8 Author Orcid Image ;   Kyoung-Tak Kang2, 3, 4 Author Orcid Image
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Journals

  1. Li L, Xing Y, Xiong W, Liao S, Zou B, Sun X, Zhi L. SwMrNet: A Multi-Target Tissue Segmentation Method for Robust and Accurate Clinical Knee Diagnosis Assistance. Bioengineering 2026;13(7):784 View